Triple
T22090251
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | The School for Good and Evil |
E545893
|
entity |
| Predicate | castMember |
P1668
|
FINISHED |
| Object | Kit Young |
—
|
NE NERFINISHED |
How this triple was built (2 steps)
Every LLM step that produced this triple, in pipeline order — named-entity classification, the disambiguation choices (the exact options shown, with the pick highlighted), and the generated description. The batch + timestamp of each is in the Provenance table below.
NER
Named-entity recognition
gpt-5-mini
Instruction
Given a phrase, classify it is english named entity (e.g., persons, organizations, works of art) in Latin script, or not (e.g., literals, dates, URLs, verbose phrases). For disambiguation, the statement where the phrase occurs as object is also given. Please return a JSON object with `phrase` (string, the phrase being analyzed) and `is_ne` (boolean, indicating whether the phrase is a Named Entity).
Input
Phrase: Kit Young | Statement: [The School for Good and Evil, castMember, Kit Young]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Kit Young Context triple: [The School for Good and Evil, castMember, Kit Young]
-
A.
Kit Young
chosen
Kit Young is a British actor best known for playing Jesper Fahey in the Netflix fantasy series "Shadow and Bone."
-
B.
Sarah Natochenny
Sarah Natochenny is an American voice actress best known for voicing Ash Ketchum in the English-language version of the Pokémon anime series.
-
C.
Bel Rowley
Bel Rowley is an ambitious and pioneering television news producer in the 1950s BBC drama series "The Hour," known for her determination, intelligence, and complex personal relationships amid a changing media landscape.
-
D.
Alexis Mann
Alexis Mann is known as one of the children of American film and television director Daniel Mann.
-
E.
Rebecca Gilman
Rebecca Gilman is an American playwright known for her socially conscious dramas that tackle issues such as class, race, and gender, including works like "Spinning into Butter" and "Boy Gets Girl."
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (2 batches)
The batch behind each pipeline step, in order, with when it ran. Timestamps are batch-level — stages were processed in waves, so the object chain (NER → NED1 → NEDg → NED2) reads in order, but predicate / elicitation batches can sit in a different wave.
| Step | Stage | Batch ID | Status | When |
|---|---|---|---|---|
| creating | Elicitation | batch_69e11e36d03c8190a83a1ba802b7231b |
completed | April 16, 2026, 5:36 p.m. |
| NER | Named-entity recognition | batch_69f128e53dfc81909858cdad8b09c5fb |
completed | April 28, 2026, 9:38 p.m. |
Created at: April 16, 2026, 8:29 p.m.